Within the field of computing, many scenarios involve an identification of an individual using one or more biometrics. As a first example, a camera may capture an image or video recording of the individual, may evaluate various visible aspects of the individual (e.g., facial features, body shape, and gait), and may generate a set of visible biometrics that represent the individual. As a second example, a microphone may capture and evaluate the voice of the individual, and various biometrics may be identified based on the acoustic properties of the voice (e.g., pitch, timbre, and rate of speech). As a third example, a fingerprint scanner may capture and evaluate a fingerprint of the individual, and biometrics relating to the pattern of ridges and whorls of the fingerprint may be identified. These analyses may be initially performed to capture one or more biometrics identifying the individual, and may be stored, e.g., in a biometric database associating the biometrics with an individual identity of the individual. Later, when an unidentified individual is detected, various biometrics may be captured and compared with those in the biometric database to identify the individual. Such capturing and identification may involve multiple biometrics (either of the same modality, e.g., multiple biometric measurements of the face of the individual, or of different modalities, e.g., a facial feature, a fingerprint, and a voiceprint of the individual) in order to improve the accuracy of the identification.